Pandas notes - Revision history

Leo: /* Importing and setup */

2018-09-20T22:17:10Z

Importing and setup

← Older revision		Revision as of 22:17, 20 September 2018
Line 8:		Line 8:
	import matplotlib.pyplot as plt		import matplotlib.pyplot as plt
	import matplotlib		import matplotlib
	matplotlib.rc('figure', figsize=(15, 5))


	== Data manipulation ==		== Data manipulation ==

2017-10-26T12:55:46Z

Data manipulation

← Older revision		Revision as of 12:55, 26 October 2017
Line 31:		Line 31:

	df = pd.DataFrame( rows )		df = pd.DataFrame( rows )

			Remove a column
			columns = ['Col1', 'Col2', ...]
			df.drop(columns, inplace=True, axis=1)

	== Plot options ==		== Plot options ==

2017-10-26T12:40:22Z

Plot options

← Older revision		Revision as of 12:40, 26 October 2017
Line 33:		Line 33:

	== Plot options ==		== Plot options ==
	Many https://pandas.pydata.org/pandas-docs/stable/visualization.html visualization examples are here].		Many [https://pandas.pydata.org/pandas-docs/stable/visualization.html visualization examples are here].

	Define the colors of the plot data		Define the colors of the plot data

2017-10-26T12:40:10Z

Plot options

← Older revision		Revision as of 12:40, 26 October 2017
Line 33:		Line 33:

	== Plot options ==		== Plot options ==
			Many https://pandas.pydata.org/pandas-docs/stable/visualization.html visualization examples are here].

	Define the colors of the plot data		Define the colors of the plot data

2017-10-26T12:09:00Z

Data manipulation

2017-10-26T12:08:49Z

Data manipulation

← Older revision		Revision as of 12:08, 26 October 2017
Line 24:		Line 24:
	dfTags = df.pivot(columns='Tagid', values='RSSI')		dfTags = df.pivot(columns='Tagid', values='RSSI')

			Creating a data frame on the run:
			rows = []
			for x in mylist :
			rec = {"Name" : x, "AA" : aa(x), "BB" : bb(x)}
			rows.append(rec)

			df = pd.DataFrame( rows )

	== Plot options ==		== Plot options ==

2017-10-26T12:04:22Z

@@ Line 1: / Line 1: @@
 {{TocRight}}
 Using [http://pandas.pydata.org/ Python Pandas package] for data analysis. Leo's notes.
 == Data manipulation ==
@@ Line 44: / Line 53: @@
 Plotting with various parameters:
- p = mymean.plot(figsize=(15,5),legend=False,kind="bar",rot=45,color="green",fontsize=16,yerr=mystd);
+ p = mymean.plot(figsize=(15,5), legend=False, kind="bar", rot=45, color="green", fontsize=16, yerr=mystd);

2017-10-26T12:02:39Z

Plot options

← Older revision		Revision as of 12:02, 26 October 2017
Line 39:		Line 39:

	Plotting means and std: [https://megapteraphile.wordpress.com/2015/11/03/plotting-means-and-stds-with-pandas/ link]		Plotting means and std: [https://megapteraphile.wordpress.com/2015/11/03/plotting-means-and-stds-with-pandas/ link]
			mymean = byTagAnt.RSSI.mean()
			mystd = byTagAnt.RSSI.std()
			mymean.plot(kind="bar", yerr=mystd);

			Plotting with various parameters:
			p = mymean.plot(figsize=(15,5),legend=False,kind="bar",rot=45,color="green",fontsize=16,yerr=mystd);

2017-10-26T11:53:28Z

Plot options

← Older revision		Revision as of 11:53, 26 October 2017
Line 37:		Line 37:
	ax = df.plot()		ax = df.plot()
	ax.legend_.remove()		ax.legend_.remove()

			Plotting means and std: [https://megapteraphile.wordpress.com/2015/11/03/plotting-means-and-stds-with-pandas/ link]

2017-10-26T07:45:06Z

← Older revision		Revision as of 07:45, 26 October 2017
Line 1:		Line 1:
			{{TocRight}}
	Using Python Pandas package for data analysis. Leo's notes.		Using [http://pandas.pydata.org/ Python Pandas package] for data analysis. Leo's notes.

			== Data manipulation ==
			Import data from a CSV file to a dataframe
			df = pd.read_csv("filename.csv")

			Filter the data by a field value
			df2 = df.loc[df['Tagid'] == "1234"]

			Get all unique values (for example, for the Tagid field)
			allTags = df.Tagid.unique()

			Pivot the table, where the values become columns. For example, to create a plot that uses unique values (of Tagid) as the series.
			dfTags = df.pivot(columns='Tagid', values='RSSI')


	== Plot options ==		== Plot options ==